Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.3-Codex-Spark is clearly ahead on the aggregate, 87 to 64. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.3-Codex-Spark's sharpest advantage is in coding, where it averages 82.3 against 43.8. The single biggest benchmark swing on the page is LiveCodeBench, 80 to 41.
Nemotron 3 Ultra 500B gives you the larger context window at 10M, compared with 256K for GPT-5.3-Codex-Spark.
Pick GPT-5.3-Codex-Spark if you want the stronger benchmark profile. Nemotron 3 Ultra 500B only becomes the better choice if you need the larger 10M context window.
GPT-5.3-Codex-Spark
85.6
Nemotron 3 Ultra 500B
62.8
GPT-5.3-Codex-Spark
82.3
Nemotron 3 Ultra 500B
43.8
GPT-5.3-Codex-Spark
88.3
Nemotron 3 Ultra 500B
66.9
GPT-5.3-Codex-Spark
92.7
Nemotron 3 Ultra 500B
77.2
GPT-5.3-Codex-Spark
78.3
Nemotron 3 Ultra 500B
57
GPT-5.3-Codex-Spark
92
Nemotron 3 Ultra 500B
84
GPT-5.3-Codex-Spark
90.8
Nemotron 3 Ultra 500B
79.7
GPT-5.3-Codex-Spark
96.7
Nemotron 3 Ultra 500B
78
GPT-5.3-Codex-Spark is ahead overall, 87 to 64. The biggest single separator in this matchup is LiveCodeBench, where the scores are 80 and 41.
GPT-5.3-Codex-Spark has the edge for knowledge tasks in this comparison, averaging 78.3 versus 57. Inside this category, HLE is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for coding in this comparison, averaging 82.3 versus 43.8. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for math in this comparison, averaging 96.7 versus 78. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for reasoning in this comparison, averaging 92.7 versus 77.2. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for agentic tasks in this comparison, averaging 85.6 versus 62.8. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for multimodal and grounded tasks in this comparison, averaging 88.3 versus 66.9. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for instruction following in this comparison, averaging 92 versus 84. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for multilingual tasks in this comparison, averaging 90.8 versus 79.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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